The quality of rubber and plastic products containing reinforcing pigments or fillers is highly dependent on the uniform dispersion of these materials throughout the polymer matrix. Dispersion occurs as particles of matter separate and become uniformly scattered throughout a medium. The dispersion of a filler in a polymer matrix can be defined by the distribution of the size of the filler entities and the distribution of the distance between the filler entities. The measurement of particle dispersion in polymers is important in order to avoid detrimental aspects of poor dispersion, such as reduced product life, poor performance during service, poor product appearance, poor processing characteristics and poor product uniformity. When a compound must be scrapped because of poor quality, there is also a combined waste of raw materials, energy used to mix the compound and production time, as well as the cost of waste disposal.
Carbon black is the primary reinforcing filler for rubber and provides such properties as improved strength, fatigue resistance, extensibility and abrasion resistance. To maximize the reinforcing effect, it is essential to establish good dispersion of the carbon black in the polymer matrix. Therefore, most of the reported methods for establishing the degree of filler dispersion in polymers have been described with respect to carbon black in rubber. However, other fillers may also be added to rubber, such as magnesium oxide, zinc oxide, titanium dioxide, silica, clay, talc, iron oxide, and the like.
The characteristic size ranges of the entities of reinforcing carbon black for rubber processing are pellets (millimeters), agglomerates (.about.10 microns), aggregates (.about.0.1 microns) and primary particles (.about.30 nanometers). Aggregates comprise a number of primary particles strongly fused together and are the basic unit of carbon black as it is formed in the furnace. Individual aggregates exhibit a natural cohesiveness for each other to form clusters (agglomerates) that can exist as hard lumps or packed dry powder that has not been wetted by the polymer. One objective of rubber processing is to overcome this cohesiveness and to disperse carbon black into rubber to as near the individual aggregate size as possible. Of the carbon black entities, it is large agglomerates that give rise to poor performance, such as tread wear resistance, higher hysteresis and earlier failure in dynamic applications. Large agglomerates are known to act as sites of flaw initiation and localized failure as the inherent flaw size for natural rubber is about 10 microns. Thus, dispersion is generally considered adequate when 95 percent of the agglomerates are below 10 microns in diameter.
Methods for assessing the quality of dispersion of fillers in rubber and other polymers have been investigated since about 1909, and include both direct and indirect methods to measure macrodispersion (particles greater than 10 microns) and/or microdispersion (particles less than 10 microns). Direct methods, such as visual surface inspection, optical microscopy, and surface roughness techniques measure macrodispersion; whereas microradiography, transmission electron microscopy and scanning electron microscopy measure microdispersion as well as macrodispersion. Sample preparation includes preparation of thin sections with a microtome using steel, glass or diamond knives; cryosections; cutting, tearing or stretching of samples; thinly extruding polymer tapes; and preparation of melted samples, such as thermoplastics, or of liquid dispersions, such as paints and inks, for examination on glass slides. Indirect methods that typically measure microdispersion include measuring the AC electrical conductivity or the microwave energy absorption of unvulcanized rubber samples, and dark field microscopic illumination to determine light scattering of the cut surface of a sample. Each of the above methods, however, is time-consuming and highly dependent on the quality of sample preparation. Moreover, optical methods are generally subjective because of a reliance on a comparison between the operator-observed dispersion and reference dispersion classification charts. Thus, these methods have only a poor to moderate accuracy. In addition, methods employing microradiography or electron microscopy are expensive.
With the recent availability of personal computers, video microscopes and computerized image analysis, several new methods for dispersion analysis have been reported. One method employs a surface finish measuring instrument, such as a stylus, to measure the peaks and valleys on the surface of a cut rubber sample. The roughness of the surface is then correlated to dispersion quality by a real-time computer software program. Although this method is fast, it measures only macrodispersion and does not provide an accurate measure of particle size and/or frequency because it does not distinguish agglomerates and aggregates from air spaces and sample cutting artifacts.
Recently reported optical methods of dispersion measurement employ a light microscope coupled with a digital imaging system. One such method is based on reflected light microscopy of the cut surface of a vulcanized rubber sample at a magnification of about 30.times. and comparison of the test sample with a reference sample when both are projected onto a split screen television monitor. The test sample is subjectively graded by the operator to the nearest reference sample and assigned a grade in a range from 1 (very bad dispersion) to 10 (absence of agglomerates that can be resolved at 30.times. magnification). This method is highly subjective and does not provide information on particle size or the distribution of differently sized particles.
Other optical methods for dispersion analysis employ imaging systems and computer software concepts similar to that used by the medical community to enhance computer assisted tomography (CAT) scan images and in tissue and blood-counting procedures. In one reported method, the rubber specimen is hardened with molten sulfur overnight and polished with metallic grinding agents to produce a mirror-like surface. The image of the surface is passed from a microscope to a photo multiplier and measurements are made of the light intensity reflecting off the specimen surface, with undispersed agglomerates having a higher reflectance than carbon black dispersed in the polymer matrix. The differences in optical density between the carbon-black agglomerates and the matrix are used to define the boundaries of the agglomerates and their size and spatial distribution, as measured by means of computer software pixel imaging analysis, and the percent carbon black dispersed on a volume basis calculated. This method is more accurate than subjective methods. However, the sample preparation requires a minimum of 16 hours due to the overnight treatment of the sample in molten sulfur. Therefore, this method has been recommended by its originators as a research and development tool, rather than to provide a more immediate dispersion analysis in the production environment.
Another method employs dark-field illumination coupled with a videomicroscope at a monitor magnification of 260.times. with field sizes of about one square millimeter and a computer image analysis software package. The data are processed on a spreadsheet, such as Quattro Pro. The method measures both macrodispersion and microdispersion with reasonable accuracy.
However, the method is highly dependent on the quality of the sample cut and the originators of this method also recommend that this method be used in a research setting.
Another method for measuring carbon black dispersion by computer imaging is currently used to grade carbon blacks according to their dispersability in a transparent polymer, such as ethylene vinyl acetate. By this method, particle dispersion in a transparent polymer tape is rated by an automated surface inspection technique that quantifies tape defects. The tape is driven by a spool system that produces enough tension on the tape to maintain a flat surface as the tape moves. A video camera constantly scans the tape and transmits the signal to a TV monitor and a computer image analysis system. The computer software corrects for die lines and scratches and selects and measures the defects by size. A plurality of tape images are then superimposed to form a compilation image of the defects and histograms of counts versus size and counts per unit area are produced. This method is also more accurate than subjective methods, but it requires that dispersion be measured in a transparent polymer, not in a rubber product.
In spite of the past and ongoing efforts to achieve a practical and accurate method for particle dispersion analysis, none of the reported methods provides a quantitative quality control test measurement for a product in a production setting.
There is a need, therefore, for a fast, non-subjective, inexpensive, accurate method for quantitatively measuring the dispersion of particles in a polymer, especially the dispersion of filler particles such as carbon black, in a processed rubber sample. Moreover, there is a need for a particle dispersion measurement method that can be used in the production environment to provide quality control of products and product uniformity from batch to batch.